Evaluating CMIP5 model agreement for multiple drought metrics

A. M. Ukkola*, A. J. Pitman, M. G. De Kauwe, G. Abramowitz, N. Herger, J. P. Evans, M. Decker

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

35 Citations (Scopus)

Abstract

Global climate models play an important role in quantifying past and projecting future changes in drought. Previous studies have pointed to shortcomings in these models for simulating droughts, but systematic evaluation of their level of agreement has been limited. Here, historical simulations (1950-2004) for 20 models from the latest Coupled Model Intercomparison Project (CMIP5) were analyzed for a variety of drought metrics and thresholds using a standardized drought index. Model agreement was investigated for different types of drought (precipitation, runoff, and soil moisture) and how this varied with drought severity and duration. At the global scale, climate models were shown to agree well on most precipitation drought metrics, but systematically underestimated precipitation drought intensity compared to observations. Conversely, simulated runoff and soil moisture droughts varied significantly across models, particularly for intensity. Differences in precipitation simulations were found to explain model differences in runoff and soil moisture drought metrics over some regions, but predominantly with respect to drought intensity. This suggests it is insufficient to evaluate models for precipitation droughts to increase confidence in model performance for other types of drought. This study shows large but metric-dependent discrepancies in CMIP5 for modeling different types of droughts that relate strongly to the component models (i.e., atmospheric or land surface scheme) used in the coupled modeling systems. Our results point to a need to consider multiple models in drought impact studies to account for high model uncertainties.

Original languageEnglish
Pages (from-to)969-988
Number of pages20
JournalJournal of Hydrometeorology
Volume19
Issue number6
DOIs
Publication statusPublished - 1 Jun 2018

Bibliographical note

Funding Information:
This work was supported by the Australian Research Council Centre of Excellence for Climate System Science (CE110001028). A. J. Pitman and M. G. De Kauwe acknowledge support from the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023).Weacknowledge the National Computational Infrastructure at the Australian National University and the Earth System Grid Federation for making the CMIP5 model outputs available. We also gratefully acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The GPCC precipitation data were acquired from NOAA/OAR/ESRL PSD, Boulder, Colorado (http://www.esrl.noaa.gov/psd/).

Funding Information:
Acknowledgments. This work was supported by the Australian Research Council Centre of Excellence for Climate System Science (CE110001028). A. J. Pitman and M. G. De Kauwe acknowledge support from the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). We acknowledge the National Computational Infrastructure at the Australian National University and the Earth System Grid Federation for making the CMIP5 model outputs available. We also gratefully acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The GPCC precipitation data were acquired from NOAA/OAR/ESRL PSD, Boulder, Colorado (http://www.esrl.noaa.gov/psd/).

Publisher Copyright:
© 2018 American Meteorological Society.

Keywords

  • Climate models
  • Drought
  • Hydrology
  • Model evaluation/performance

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